Proposed a model to evaluate supply chains sustainability efficiency based on trade-offs among sustainability goals using game theory
Subject Areas :
Industrial Management
Mohsen Yaghoubizade Vanini
1
,
Reza Yousefi Zenouz
2
,
Amir-Reza Abtahi
3
,
Kaveh Khalili-Damghani
4
1 - PhD candidate, Department of Industrial Engineering, South Tehran Branch, Islamic Azad University
2 - Assistant Professor, Information Technology and Operations Management, Kharazmi University
3 - Assistant Professor, Information Technology and Operations Management, Kharazmi University
4 - Associate Professor, Department of Industrial Engineering, South-Tehran Branch, Islamic Azad University
Received: 2022-07-05
Accepted : 2022-09-12
Published : 2023-02-20
Keywords:
Supply Chain Sustainability,
efficiency evaluation,
Game Theory,
Abstract :
Supply chain sustainability is necessary for businesses today, so organizations pay attention to social and environmental goals in addition to economic goals. Therefore, to ensure the realization of these goals, measuring the sustainability efficiency of the supply chain is considered inevitable. The problem of assessing the performance of supply chain sustainability, on the one hand, is affected by the inherent conflicts of interest among sustainability goals, which increase the complexity of the problem, and on the other hand, it should be configured in a way that can simultaneously provide sufficient knowledge of the efficiency of overall supply chain sustainability and sustainability goals. In this study, a combined mathematical model of data envelopment analysis and game theory is presented to evaluate the sustainability efficiency of the supply chain and the efficiency of sustainability goals by considering the trade-offs among sustainability goals. The trade-offs among sustainability goals are formulated using the Nash bargaining game in such a way that the ability to provide simultaneous results is related to the overall efficiency of supply chain sustainability and the efficiency of each sustainability goal. The proposed model was evaluated under a case study for appraising the efficiency of supply chain sustainability of an Iranian pharmaceutical company. The results of the model implementation indicate that the proposed model is firstly capable of simultaneously providing efficiency values of supply chain sustainability and each sustainability goal, and secondly, it provides the necessary and sufficient knowledge in comparison of these values for efficient and inefficient products.
References:
Acquaye, A., Ibn-Mohammed, T., Genovese, A., Afrifa, G. A., Yamoah, F. A., & Oppon, E. (2018). A quantitative model for environmentally sustainable supply chain performance measurement. European Journal of Operational Research, 269(1), 188-205.
Amirkhan, M., Didehkhani, H., Khalili-Damghani, K., & Hafezalkotob, A. (2018). Measuring performance of a three-stage network structure using data envelopment analysis and Nash bargaining game: a supply chain application. International Journal of Information Technology & Decision Making, 17(05), 1429-1467.
Badiezadeh, T., Saen, R. F., & Samavati, T. (2018). Assessing sustainability of supply chains by double frontier network DEA: A big data approach. Computers & Operations Research, 98, 284-290.
Beckmann, M., Hielscher, S., & Pies, I. (2014). Commitment strategies for sustainability: How business firms can transform trade‐offs into win–win outcomes. Business Strategy and the Environment, 23(1), 18-37.
Beske-Janssen, P., Johnson, M. P., & Schaltegger, S. (2015). 20 years of performance measurement in sustainable supply chain management–what has been achieved? Supply chain management: An international Journal, 20, 664-680.
Chithambaranathan, P., Subramanian, N., Gunasekaran, A., & Palaniappan, P. K. (2015). Service supply chain environmental performance evaluation using grey based hybrid MCDM approach. International Journal of Production Economics, 166, 163-176.
Dumitrascu, O., Dumitrascu, M., & Dobrotǎ, D. (2020). Performance evaluation for a sustainable supply chain management system in the automotive industry using artificial intelligence. Processes, 8(11), 1384.
Esfahbodi, A., Zhang, Y., & Watson, G. (2016). Sustainable supply chain management in emerging economies: Trade-offs between environmental and cost performance. International Journal of Production Economics, 181, 350-366.
Fathi, A., Karimi, B., & Saen, R. F. (2022). Sustainability assessment of supply chains by a novel robust two-stage network DEA model: a case study in the transport industry. Soft Computing, 1-18.
Haghighi, S. M., Torabi, S. A., & Ghasemi, R. (2016). An integrated approach for performance evaluation in sustainable supply chain networks (with a case study). Journal of cleaner production, 137, 579-597.
Hahn, T., Pinkse, J., Preuss, L., & Figge, F. (2015). Tensions in corporate sustainability: Towards an integrative framework. Journal of business ethics, 127(2), 297-316.
Izadikhah, M., & Saen, R. F. (2018). Assessing sustainability of supply chains by chance-constrained two-stage DEA model in the presence of undesirable factors. Computers & Operations Research, 100, 343-367.
Jakhar, S. K. (2015). Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry. Journal of Cleaner Production, 87, 391-413.
Jomthanachai, S., Wong, W. P., & Lim, C. P. (2021). A Coherent Data Envelopment Analysis to Evaluate the Efficiency of Sustainable Supply Chains. IEEE Transactions on Engineering Management.
Jørgensen, T. H. (2008). Towards more sustainable management systems: through life cycle management and integration. Journal of cleaner production, 16(10), 1071-1080.
Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA models for supply chain efficiency evaluation. Annals of operations research, 145(1), 35-49.
Mahmoudi, R., Emrouznejad, A., & Rasti-Barzoki, M. (2019). A bargaining game model for performance assessment in network DEA considering sub-networks: a real case study in banking. Neural Computing and Applications, 31(10), 6429-6447.
Mirhedayatian, S. M., Azadi, M., & Saen, R. F. (2014). A novel network data envelopment analysis model for evaluating green supply chain management. International Journal of Production Economics, 147, 544-554.
Morhardt, J. E., Baird, S., & Freeman, K. (2002). Scoring corporate environmental and sustainability reports using GRI 2000, ISO 14031 and other criteria. Corporate Social Responsibility and Environmental Management, 9(4), 215-233.
Narimissa, O., Kangarani‐Farahani, A., & Molla‐Alizadeh‐Zavardehi, S. (2020). Evaluation of sustainable supply chain management performance: Indicators. Sustainable Development, 28(1), 118-131.
Qorri, A., Mujkić, Z., & Kraslawski, A. (2018). A conceptual framework for measuring sustainability performance of supply chains. Journal of Cleaner Production, 189, 570-584.
Tajbakhsh, A., & Hassini, E. (2018). Evaluating sustainability performance in fossil-fuel power plants using a two-stage data envelopment analysis. Energy Economics, 74, 154-178.
Tavassoli, M., Ketabi, S., & Ghandehari, M. (2022). A novel fuzzy network DEA model to evaluate efficiency of Iran’s electricity distribution network with sustainability considerations. Sustainable Energy Technologies and Assessments, 52, 102269.
Veleva, V., & Ellenbecker, M. (2001). Indicators of sustainable production: framework and methodology. Journal of cleaner production, 9(6), 519-549.
Wang, H., Pan, C., Wang, Q., & Zhou, P. (2020). Assessing sustainability performance of global supply chains: An input-output modeling approach. European journal of operational research, 285(1), 393-404.
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Acquaye, A., Ibn-Mohammed, T., Genovese, A., Afrifa, G. A., Yamoah, F. A., & Oppon, E. (2018). A quantitative model for environmentally sustainable supply chain performance measurement. European Journal of Operational Research, 269(1), 188-205.
Amirkhan, M., Didehkhani, H., Khalili-Damghani, K., & Hafezalkotob, A. (2018). Measuring performance of a three-stage network structure using data envelopment analysis and Nash bargaining game: a supply chain application. International Journal of Information Technology & Decision Making, 17(05), 1429-1467.
Badiezadeh, T., Saen, R. F., & Samavati, T. (2018). Assessing sustainability of supply chains by double frontier network DEA: A big data approach. Computers & Operations Research, 98, 284-290.
Beckmann, M., Hielscher, S., & Pies, I. (2014). Commitment strategies for sustainability: How business firms can transform trade‐offs into win–win outcomes. Business Strategy and the Environment, 23(1), 18-37.
Beske-Janssen, P., Johnson, M. P., & Schaltegger, S. (2015). 20 years of performance measurement in sustainable supply chain management–what has been achieved? Supply chain management: An international Journal, 20, 664-680.
Chithambaranathan, P., Subramanian, N., Gunasekaran, A., & Palaniappan, P. K. (2015). Service supply chain environmental performance evaluation using grey based hybrid MCDM approach. International Journal of Production Economics, 166, 163-176.
Dumitrascu, O., Dumitrascu, M., & Dobrotǎ, D. (2020). Performance evaluation for a sustainable supply chain management system in the automotive industry using artificial intelligence. Processes, 8(11), 1384.
Esfahbodi, A., Zhang, Y., & Watson, G. (2016). Sustainable supply chain management in emerging economies: Trade-offs between environmental and cost performance. International Journal of Production Economics, 181, 350-366.
Fathi, A., Karimi, B., & Saen, R. F. (2022). Sustainability assessment of supply chains by a novel robust two-stage network DEA model: a case study in the transport industry. Soft Computing, 1-18.
Haghighi, S. M., Torabi, S. A., & Ghasemi, R. (2016). An integrated approach for performance evaluation in sustainable supply chain networks (with a case study). Journal of cleaner production, 137, 579-597.
Hahn, T., Pinkse, J., Preuss, L., & Figge, F. (2015). Tensions in corporate sustainability: Towards an integrative framework. Journal of business ethics, 127(2), 297-316.
Izadikhah, M., & Saen, R. F. (2018). Assessing sustainability of supply chains by chance-constrained two-stage DEA model in the presence of undesirable factors. Computers & Operations Research, 100, 343-367.
Jakhar, S. K. (2015). Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry. Journal of Cleaner Production, 87, 391-413.
Jomthanachai, S., Wong, W. P., & Lim, C. P. (2021). A Coherent Data Envelopment Analysis to Evaluate the Efficiency of Sustainable Supply Chains. IEEE Transactions on Engineering Management.
Jørgensen, T. H. (2008). Towards more sustainable management systems: through life cycle management and integration. Journal of cleaner production, 16(10), 1071-1080.
Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA models for supply chain efficiency evaluation. Annals of operations research, 145(1), 35-49.
Mahmoudi, R., Emrouznejad, A., & Rasti-Barzoki, M. (2019). A bargaining game model for performance assessment in network DEA considering sub-networks: a real case study in banking. Neural Computing and Applications, 31(10), 6429-6447.
Mirhedayatian, S. M., Azadi, M., & Saen, R. F. (2014). A novel network data envelopment analysis model for evaluating green supply chain management. International Journal of Production Economics, 147, 544-554.
Morhardt, J. E., Baird, S., & Freeman, K. (2002). Scoring corporate environmental and sustainability reports using GRI 2000, ISO 14031 and other criteria. Corporate Social Responsibility and Environmental Management, 9(4), 215-233.
Narimissa, O., Kangarani‐Farahani, A., & Molla‐Alizadeh‐Zavardehi, S. (2020). Evaluation of sustainable supply chain management performance: Indicators. Sustainable Development, 28(1), 118-131.
Qorri, A., Mujkić, Z., & Kraslawski, A. (2018). A conceptual framework for measuring sustainability performance of supply chains. Journal of Cleaner Production, 189, 570-584.
Tajbakhsh, A., & Hassini, E. (2018). Evaluating sustainability performance in fossil-fuel power plants using a two-stage data envelopment analysis. Energy Economics, 74, 154-178.
Tavassoli, M., Ketabi, S., & Ghandehari, M. (2022). A novel fuzzy network DEA model to evaluate efficiency of Iran’s electricity distribution network with sustainability considerations. Sustainable Energy Technologies and Assessments, 52, 102269.
Veleva, V., & Ellenbecker, M. (2001). Indicators of sustainable production: framework and methodology. Journal of cleaner production, 9(6), 519-549.
Wang, H., Pan, C., Wang, Q., & Zhou, P. (2020). Assessing sustainability performance of global supply chains: An input-output modeling approach. European journal of operational research, 285(1), 393-404.